Location-based information was traditionally a simplistic association between a given location (e.g. street address) and information about the tenants or uses of that location. For example, the location identified by the address 123 Elm street could be associated with a resident of that location (e.g. John Smith), or a business at that location (e.g. a motorcycle shop under the name Dave's Bikes), along with a telephone number. This association was traditionally published in telephone phone books, with listings by residential name, business name and/or business category. Some locations include multiple tenants or uses. For these locations, a floor, suite, unit or apartment number was traditionally used to differentiate one tenant/use from another at the same address location.
With the advent of the Internet, wireless networks, and portable electronic devices, there has been an explosion of location-based information that can be created, stored and disseminated. The problem arises as to how to collect and organize this information for each location, and/or for each of the tenants/uses at each location, so that the information can be accessed and used in an efficient manner. For example, take the simple situation of a location having an address of “123 Main Street, Anytown, USA”, which has a building with multiple tenants: a restaurant (named “The Restaurant”) on the first floor, an advertising agency (named “The Agency”) on the second floor, and a personal residence (“The Residence”) on the third floor. There are various types of location-based information for these tenants, some shared and some unique. For example, each tenant has the same location information associated with it (e.g. the 123 Main Street address), as well as unique location information (e.g. the floor/suite/unit/apartment number, telephone number, business type, business hours, etc.). Other information can be associated just with The Restaurant (e.g. food reviews, event listings, business WiFi access, other publicity, etc.), with just The Agency (articles, campaigns, client reviews, business WiFi access, other publicity, etc.), and with just The Residence (e.g. personal information, personal WiFi access, other publicity, etc.). Building or neighborhood information can be associated with one, two or all three tenants. Collecting, associating and sharing location based information is problematic since all three tenants share the same location.
To make matters even more confusing, there are numerous ways to make reference to a single tenant at a location. For example, each tenant can be referenced by a suite number, by a floor number, by an abbreviated name, by a full name, etc. Moreover, the address itself can be expressed in different ways, such as 123 Main Street, 123 Main St., 123 Main, etc. Lastly, various commercial entities use different ID schemes to identify the same location or tenant. For example, a delivery company may use one ID code for The Restaurant, while an events website may use another ID code for The Restaurant at which events are occurring. When different schemes are used to identify the same location, and/or the same tenant at that location, it becomes difficult to receive information about that location from various sources, properly associate the information with the location and/or its tenants, and share that associated information with others.
There is a need for a system and method that can efficiently and accurately associate electronic information with the relevant location(s), and provide, link or point to that electronic information based upon that association, especially when the identified location itself is insufficient to adequately associate the information to the proper tenant/use of that location.